AI is anticipated to enhance human decision-making in high-stakes domains like aviation, but adoption is often hindered by challenges such as inappropriate reliance and poor alignment with users' decision-making. Recent research suggests that a core ...

Explaining the mechanisms behind model predictions is a common strategy in AI-assisted decision-making to help users rely appropriately on AI. However, recent research shows that the effectiveness of explanations depends on numerous factors, leading to ...

Recent studies found that humans tend to overrely on AI when making decisions with AI support. AI explanations were often insufficient as mitigation, and sometimes even increased overreliance. However, typical AI-assisted decision-making studies ...

Intelligent decision support tools (DSTs) hold the promise to improve the quality of human decision-making in challenging situations like diversions in aviation. To achieve these improvements, a common goal in DST design is to calibrate decision makers’ ...

This paper demonstrates a simulation framework that collects data about connected vehicles' locations and surroundings in a realistic traffic scenario. Our focus lies on the capability to detect parking spots and their occupancy status. We use this data ...

In graph neural networks (GNNs), message passing iteratively aggregates nodes' information from their direct neighbours while neglecting the sequential nature of multi-hop node connections. Such sequential node connections e.g., metapaths, capture ...

Decision support systems based on AI are usually designed to generate complete outputs entirely automatically and to explain those to users. However, explanations, no matter how well designed, might not adequately address the output uncertainty of such ...

Classifying stress in firefighters poses challenges, such as accurate personalized labeling, unobtrusive recording, and training of adequate models. Acquisition of labeled data and verification in cage mazes or during hot trainings is time ...

The purpose of image restoration is to recover the original state of damaged images. To mitigate the disadvantages of the manual image restoration process such as the high time consumption, we present interactive Deep Image Prior by extending Deep ...

The purpose of image restoration is to recover the original state of damaged images. To overcome the disadvantages of the traditional, manual image restoration process, like the high time consumption and required domain knowledge, automatic inpainting ...

Integrated Development Environments (IDEs) are used for a varietyof software development tasks. Their complexity makes them chal-lenging to use though, especially for less experienced developers. In this paper, we outline our approach for an user-...

Driving in autonomous cars requires trust, especially in case of unexpected driving behavior of the vehicle. This work evaluates mental models that experts and non-expert users have of autonomous driving to provide an explanation of the vehicle's past ...

Situation awareness in highly automated vehicles can help the driver to get back in the loop during a take-over request (TOR). We propose to present the driver a detailed digital representation of situations causing a TOR via a scaled down digital twin ...